Determining Energy Consumption in a Structure

ABSTRACT

Methods, apparatus, and systems are provided for measuring the supply of a consumable product/energy source, such as electrical power, to a facility over time and analyzing the measurements to determine the consumption or supply of the product by one or more loads and/or sources in the facility, and to determine induced and residual heat flow through the facility&#39;s envelope. Various aspects compare the measured supply of the consumable product to a database of consumption signatures, which characterize access to the consumable product by particular users. Operating conditions and facility characteristics, such as temperatures, load factors, insulation factors, etc., may be further considered in determining a particular user&#39;s access of the consumable product. To aid in the controlling of energy use, thermal resistance factors of the building are determined, which are based on the induced and residual heat flow through the facility.

This application is a divisional of U.S. patent application Ser. No.12/960,149, filed Dec. 3, 2010, entitled Determining Energy Consumptionin a Structure, which is a continuation-in-part of U.S. patentapplication Ser. No. 12/557,992, filed Sep. 11, 2009, entitledDetermining Consumption and/or Generation of Consumable Products in aDistributed System. The above referenced applications are incorporatedherein by reference in their entireties.

FIELD OF THE DISCLOSURE

Aspects relate generally to measuring consumption and production of aconsumable product in a distribution system by one or more loads and/orsources. Further aspects relate generally to measuring energy efficiencyof buildings via direct measurements as opposed to calculatedtheoretical measurements and/or utilizing these direct measurements inincentive based construction contracts. Methods, apparatus, and systemsare disclosed which determine access to the consumable product (e.g.,electricity) by a particular load or source in the distribution systemthrough the use of techniques which characterize consumption/generationof the consumable product by one or more of the loads or sources. Themethods, apparatus, and systems further provide real time monitoring ofenvironmental conditions and usage of a building to characterize thebuilding's current and historical energy performance and/or R-value.

BACKGROUND

Utility costs represent one of the largest expenses effecting netoperating cost of residential, commercial, and industrial facilities.For example, a large office building comprised of 60,000 square feetwill have an electrical consumption of approximately $10,000 monthly inthe Mid Atlantic states in the summer months. Knowing how a building isbeing utilized by its tenants and knowing the building energyperformance are both factors in understanding and controlling thesecosts.

SUMMARY

With respect to building utilization, tenants are constantly connectingelectrical consumption devices including servers and other electricequipment not only to dedicated tenant lines but also to building powerlines. Being able to recover this cost from tenants of the facility iscritical to maximizing value, maximizing loan capacity of the facility,and maximizing revenue stream generated from the facility. However,being able to accurately match the consumption of utilities such aselectrical power to individual tenants and/or buildings is oftendifficult. Further, some tenants and/or buildings will provide forgeneration of power for input into a smart grid. These generationfacilities may include, for example, solar panels and/or wind generationfacilities located proximate to buildings such as on top of buildings.There is a need to account for these installations. Additionally,electrical power, which is distributed to a number of tenants, may beprovided to a facility with one supply service measured by one meter. Torecover the cost of the electrical power, the facility manager may haveto install costly additional supply services and meters or retro-fit theelectrical distribution system in the facility such that each tenantselectrical usage can be measured individually. Alternatively, the costof the utility may be averaged and allocated to each tenant equally.

Situations may arise where one tenant consumes a disproportionate amountof the utility. For example, a particular tenant may install highpowered add-on equipment such as computer server rooms, laboratorysystems, or cellular network towers. In such cases, the facilityoperator may find that averaging the utility cost across all of thetenants may push the facility's fixed cost per square-foot to be greaterthan the facility's value per square-foot.

Building systems lack a simple understandable method for tracking theutility consumption. Due to the inability to simply track theconsumption, building automation systems are often removed from service,electrically jumpered out of the distribution system, adjusted to extendstart and stop times beyond optimal settings, not adjusted to reflectchanges in the hours of occupancy from the original lease schedule,etc., and thus, the facility consumes more energy due to inadequatecontrols and monitoring. One technique to monitor and control theconsumption is, for example, a graphical user interface which may bevariously configured. In exemplary embodiments, it may be configured tocompare historical values (as for example adjusted for outsidetemperature) with current values. The graphical user interface mayemploy an appropriate algorithm and graphical representations showingdeviations which likely indicate either a problem or new energy usage bya particular tenant.

Another factor in controlling energy costs is understanding the thermalperformance of the building's envelope (i.e., structure). Improvingenergy efficiency in new construction and in the remodeling of existingstructures has become a primary concern, which is driven by such factorsas utility costs, public concern for the environment and human health,government regulation, corporate social responsibility, globalization,and other market forces. In response to this concern, industry groupshave formed, which put forth efficiency guidelines and certificationprograms for builders to follow. These certifications and other designbenchmarks require energy efficiency to be addressed early in the designand construction process.

These requirements and verifications typical are based on simulation ofbuilding models, and an as-built structure may not, and often does not,meet the energy performance requirements of the planned design onday-one after completion. The errors in the simulation may be caused bydesign variations that are not reflected in the model, construction ofthe structure which is not to specification, incorrect assumptions onbuilding usage and weather, utility equipment which is not installedcorrectly or functioning according to specification, insufficient modelfidelity, and numerous other factors. Further, a building's energyperformance may change over time due to the aging of materials,modifications to building structures and systems, or damage to thestructures and systems.

Currently, no means exist to comprehensively measure a building's actualenergy performance or to monitor the energy performance over time. Thus,the verification and management of a building's designed energyefficiency is based on incomplete or inaccurate information.

To overcome these problems described above and other problems, methodsand systems are needed to determine the use of a utility by individualtenants, and to provide comprehensive in-situ measurement of abuilding's actual energy performance. These techniques allow buildingdevelopers to insert incentive provisions in their contracts to ensurethat buildings actually meet their design requirements. The end resultmay be specified without micromanaging the building process. This allowsthe building process to proceed as efficiently as possible and allowsnew technologies to be easily integrated without renegotiating theoverall contract.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the invention.

Various techniques are presented for measuring the supply of aconsumable product, such as electrical power, to a facility over timeand analyzing the measurements to determine the consumption or supply ofthe product by one or more loads and/or sources (i.e. users) in thefacility. Various aspects compare the measured supply of the consumableproduct to a database of signatures, and/or lease schedules whichcharacterize access to the consumable product by particular users. Inone exemplary embodiment, the supply of consumable product to the HVACsystem may be measured and analyzed as compared to the insidetemperature, outside temperature, sun loading, and heat generated byother devices such as lighting and computers to determine the overallR-value of a building.

The various techniques may be used, for example, in facilities toprovide detailed reports of the usage of utilities such as electricalpower, gas, and water, by multiple different users connected to a commonmeasurable supply of the product. In doing so, the various techniquesmay be used to more accurately divide the cost of such utilities betweendifferent tenants of the facility without having to install individualservices that can be individually measured for each tenant. In addition,by analyzing real time data and historical utility signatures the usercan modify schedules to match leases, verify equipment operation eitheron/off, and verify large equipment loads by reviewing building utilitysignatures.

In a first embodiment, measurements are made from a common service,recorded as a data sequence, and transmitted to one or more processorsfor analyses. The processor(s) may retrieve signatures from a databaseto analyze various parameters such as the data sequences and determine,for example, different parameters such as how much of the measuredproduct is consumed or produced by one or more particular users within agroup of users connected to the measured service. Reports may then begenerated which detail the use and/or supply.

In other embodiments operating conditions of the various users in thefacility are measured at the same time supply of the consumable productmay be measured. These operating conditions may be stored and/ortransmitted to the processor(s), and the processor(s) may be configuredin various ways. In one configuration, the processors may use theoperating conditions as additional data in determining the usage of theconsumable product by one or more users. Operating conditions mayinclude, for example, temperatures inside and outside of the facility,and/or the number of people in the facility. These parameters may beutilized to determine a base line and/or inform the building managerwhenever the building varies from the baseline, potentially indicatingan anomaly.

In another embodiment, artificial intelligence algorithms such as, forexample, neural networks may be used in the analysis of the datasequences and/or signatures to determine the usage of one or moreparticular users. The artificial intelligence may develop and learn overtime using both rule based input and learned input from a trainedoperator.

In other embodiments, the signatures may be created by monitoring theuse and/or supply of the consumable product in the distribution systemof a facility and comparing the monitored use and/or supply to measuredor controlled operating conditions of users of the product within thefacility. The signatures may be determined, for example, by training anartificial intelligence process such as a neural network with themeasured supply and/or operating conditions.

Further techniques are presented for measuring induced and/or residualheat flow through a building envelope. Various illustrative induced heatflows include heat resulting from: electrical power flowing into abuilding and being converted to heat by the distribution system and byelectrical loads; fuel such as natural gas flowing into the building toproduce heat when used; water which flows into the building and carriesheat by virtue of its thermal mass; climate control systems whichmechanically move heat through the building; and people which dissipateheat while inside the building. Residual heat flow includes the passiveheat transfer through the building structure which is induced by thedifference in the environments within the building and outside of thebuilding. These various induced and residual heat flows may bedetermined periodically and in real time.

In exemplary embodiments, the building may be qualified while minimizingthe transient heat flows generated by people, water, and non-HVAC heatsources such as lights and computers. This qualification may take placeboth at initial building launch and after a set period of time such asafter building buildout. Incentives may be built into the contract thatare conditioned on meeting predetermined performance criteria, such asR-value criteria. These R-value criteria may be specified with and/orwithout transient heat flows minimized.

In various embodiments, the residual heat flow and thermal resistance ofwall assemblies of the building are measured using embedded sensorswithin the wall and/or periodically using transportable sensors. In oneembodiment, the sensors are embedded in the material making up a layerof the wall assembly by the manufacturer of that material layer. Inanother embodiment, a temperature probe is inserted through the layersof the wall, wherein the probe has the ability to sense multipletemperatures at incremental depths along the probe.

In further embodiments, a thermal resistance factor of the buildingenvelope is determined based on the measured induced and/or residualheat flows. Thermal resistance factor, R_(C), is often a compositemeasure of thermal performance of a building envelope. The thermalresistance factor may be determined statically, where some or allinduced heat flow is cut off, and the inside and outside environmentsare monitored over time as they approach equilibrium with one another.In one aspect the thermal resistance factor is determined as the amountof time taken for equilibrium to be reached given predefined initialconditions. In another aspect, the thermal resistance factor is definedby the change in temperature over a given time period given at set ofinitial conditions.

In other embodiments, the thermal resistance factor may be determineddynamically, where induced heat flow and environmental conditions areperiodically and/or continuously monitored in real time.

In various embodiments, the static or dynamic thermal resistance factorsmay be used in one or more additional processes. For example, in oneembodiment, the process may utilize a one-time snapshot of thermalresistance factor and/or a thermal resistance factor determinedrepeatedly to capture changes in the thermal resistance factor overtime. In embodiments, the method of determining a target thermalresistance factor and/or a required thermal resistance factor may bespecified in a building contract as a design metric. In otherembodiments, the specific methods for determining R_(C) may be used asindustry standards to compare different structures, or to establishminimum build criteria. In still other embodiments, the thermalresistance factor may be used along with measured or forecastedenvironment conditions in a closed loop system to control the climatecontrol system of the building. For example, the closed loop system mayfurther control the climate control system and/or other building systemsbased on utility usage by different users as determined above based onuser signatures.

Other various embodiments include systems, equipment, processes, andcomputer readable memory storing machine executable instructions forperforming the functions of the embodiments described above.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the disclosure and the advantagesthereof may be acquired by referring to the following description inconsideration of the accompanying figures, in which like referencenumerals in different figures indicate similar elements, in which thefirst portion of each reference numeral corresponds to the figure numberin which the referenced element is first introduced, and wherein:

FIG. 1 illustrates an exemplary electrical distribution system of afacility in which various embodiments may be implemented;

FIG. 2 illustrates an exemplary display graph illustrating datasequences representing consumption of a consumable product in adistribution system.

FIG. 3 illustrates a flow diagram of an embodiment for determining anamount of a consumable product accessed by a user;

FIG. 4 illustrates a flow diagram of another embodiment for determiningan amount of a consumable product accessed by a user;

FIG. 5 illustrates an exemplary facility incorporating various sensorswhich may be used with various embodiments;

FIG. 6 illustrates a flow diagram of an embodiment for determiningsignatures which characterize access to a consumable product by one ormore users;

FIG. 7 illustrates a hardware block diagram of a processor according tosome embodiments.

FIG. 8 illustrates a building envelope in which various embodiments maybe implemented;

FIG. 9 illustrates heat flow through a building envelope in whichvarious embodiments may be implemented;

FIG. 10 illustrates a flow diagram of an embodiment for determining heatflow and thermal performance of a building envelope;

FIG. 11 illustrates a flow diagram of an embodiment for analyzing datasequences to determine induced heat flow from various energy sources;

FIG. 12 illustrates a flow diagram of an embodiment for measuringenvironmental conditions and self contained heat emitting bodies;

FIG. 13 illustrates an illustrative facility incorporating varioussensors which may be used with various embodiments.

FIG. 14 illustrates various embodiments of sensors and resulting sensordata.

DETAILED DESCRIPTION

In the following description of the various embodiments, reference ismade to the accompanying drawings, which form a part hereof, and whichare shown by way of illustration. It is to be understood that otherembodiments may be utilized and structural and functional modificationsmay be made without departing from the scope of the disclosure.

FIG. 1 illustrates an exemplary system 100 in which various embodimentsmay be implemented. System 100 includes an electrical distributionsystem of a facility 101 in which electrical power is distributed as aconsumable product to various electrical loads (i.e. users) connected tothe distribution system. The facility may be commercial, residential,industrial, some combination thereof, or may be any other structurewhich contains a distribution system for the supply and/or generation ofa consumable product. Exemplary facilities include apartment buildings,strip malls, office buildings, hospitals, industrial parks, etc.

A consumable product such as electrical power may be provided tofacility 101 via any suitable source such as a public, private, and/orcooperative utility through transmission lines 128 or may be generatedfrom on site sources such as solar panel 130, or back up generator 131.The utility may be provided as one supply feed 103 through a singlemeter 102, or may be supplied through several separate feeds and/ormeters. Often, a single feed is split at a distribution point 106 intoseveral separate distribution services 120-124, each of the servicesproviding one or more different users access to the utility. Exemplaryusers may include loads typically found in facilities, includinglighting 107-112 and/or heating, ventilation and/or air conditioningsystems (HVACs) 117-119. Additional non-standard loads may also beconnected to the distribution system depending on the particular use ofthe facility. Illustrative non-standard loads may include a computerserver room 114, industrial machinery 115, medical equipment 113, and/ora cellular network tower 116. Additional exemplary non-standard loadsmay include charging circuits 129 in a garage associated with electriccars. Users may inductively or via a plug-in cable charge their electriccars while parked in the garage. These charges may be billed back to theindividual parking tenant rather than distributed to all users in thebuilding. Further, during peak periods, cars in the garage may beutilized to store and resource power back into the building and/ordistribution network. Exemplary users may include producers of theconsumable product that is put back into the distribution system for useby loads locally and/or for distribution back into the transmissionlines 101. Such producers may include solar panels 130, back-upgenerators 131, batteries from electric cars, etc. which may bedistributed about the building including on the sides, within thebuilding, on the roof, and/or disposed around a building, cell tower, orother facility 101. These sources may be coupled to the distributiondevice 106 for use locally and/or input back into the system 100 viatransmission lines 128.

Distribution systems may be designed to support specific users, and/orspecific tenants of the facility who connect a specific group of usersto the distribution system. The design of the distribution system mayprovide individual tenants and individual employees of the tenant theirown supply feed, distribution service, and/or different combinationsthereof such that use and/or generation of the consumable product by theindividual tenant/employee may be uniquely measured using a meter on thetenant's/employee's supply feed or using a sub-meter on the tenant'sdistribution service. However, designing the distribution aroundspecific tenants is not always accomplished or even possible. Asrequirements for the facility change, users of the consumable productmay be added in an ad-hoc manner without accounting for how theconsumable product is shared between the tenants.

In instances where access (consumption or production) to the consumableproduct by a specific user (load or producer), or group of users, needsto be measured on a supply feed or distribution service shared withother users, some embodiments may add a meter 104 or sub-meter 105 to asupply feed or distribution service respectively, to measure and recordconsumption or supply of the consumable product over time. From thesemeasurements, analysis may be performed according to certain embodimentsto determine access to the consumable product by the user, or group ofusers, of interest, from the total access by all the users on themeasured supply feed or distribution service.

Meter 104 and sub-meter 105 may be variously configured. In oneembodiment, meter 104 and sub-meter 105 may include one or more sensorscoupled to the supply feed or distribution service used to measure thesupply of the consumable product. Various sensors appropriate formeasuring the consumption and/or supply of the consumable product willdiffer depending on the consumable product being measured. In anelectrical distribution system in system 100, the sensor may be aninductively coupled transformer, a current shunt, or other appropriatesensor for measuring the consumable product such as power, electricalcurrent and/or voltage. In other distribution systems for otherconsumable products such as natural gas and water, appropriate flowmeters may be used. Meters 104 and 105 will further include a computingplatform to operate the sensor, and accumulate pulse inputs (periodicmeasurements) from the sensors. Each meter may include several sensorsand accumulate data from several different paths in the distributionsystem. As an example, meter 104 may include a circuit board with 10sensor channels for sensors which may each collect pulse data inparallel. A processor on the circuit board may read each channel andaccumulate data in the same and/or separate memory devices (e.g.registers) for each channel. The meter 104 may further have a datadisplay which scrolls periodically and/or continuously to illustrate thepulses per channel. In addition to the data display, meter 104 may havebuttons or other inputs which can be used for on-site programming and/ortrouble shooting. After on-site programming/trouble shooting, furtherprogramming may be from a remote location and/or computer.

The meters may be variously configured. In some embodiments, the metersmay transmit data (e.g., pulse data) to a different computing platform,such as server/workstation 127 via a private network (e.g., cellularnetwork 125) and/or a public network (e.g., the Internet 126). The pulsedata from one or more sensors may be individually transmitted, and/ormay be grouped in any appropriate manner such as being totaled over auser defined and/or predefined and/or variable period and transmitted.The server/workstation 127 may further accumulate data from one and/orseveral different meters. Server/workstation 127 may be within thefacility, collocated with the meters, or remote as illustrated inFIG. 1. Each meter and server/workstation may have one or moreinterfaces to one or more communication paths to transfer data betweenthe meter and the server/workstation. Exemplary communication paths mayinclude various public and private local area networks (LAN) and widearea networks (WAN), etc., over various physical networks, includingvoice band and digital subscriber line (DSL) modems on public switchedtelephone networks (PSTN), cable and fiber-optic modems and networks,cellular phone networks, satellite networks, Wifi, Wimax, etc. Thevarious communication paths may provide a direct connection between themeters and the server/workstation, and/or may provide connection throughthe Internet via an Internet Service Provider (ISP). System 100 in FIG.1 illustrates an exemplary Internet connection 126 connecting meter 104to server/workstation 127, and an exemplary cellular phone networkconnection 125, connecting sub-meter 105 to server workstation 127.These communication paths could also, for example, include a combinationof these networks. For example, sub-meter 105 could alternatively useany suitable wireless protocol (including 802.11a/g/n, wireless internetprotocol, 3G, 4G, GSM, PHS, HC SD, TACS, CDMA, HSDPA, TDMA, CDMA2000,iDEN, TD-SCDMA, EV-DO, Mobitex, UMTS, FDMA, NMT, WCDMA, GAN, PCS, WiDEN,GPRS, PDC, WiMAX, and/or ISM band) over a network such as cellularnetwork 125 to connect the meters to each other and/or to a public orprivate network (e.g., Internet 126) and to any appropriateserver/workstation 127. For example, the ISM band may allow for eitherbattery operated and/or inductively powered meters which can operatewithout having to be plugged in and/or connected to a wired interfaceand/or power. In embodiments using an Internet protocol, meter 104 mayutilize a dynamic IP address, and, once powered and connected to theInternet via an Ethernet connection, may automatically findserver/workstation 127 on the network and register each new channel as anew user, assigning a unique address for each channel. For example, thedevice may each have an auto configure and registration mode whichallows the installer to remotely activate and register the device to aparticular building using a laptop with a wireless card and/or ahandheld smart phone like device.

The server/workstation 127 and the various meters may collect the pulsedata in a variety of ways. For example, server/workstation 127 may hosta website which may accumulate the pulses in one or more memories suchas data registers. There may be one or more memories per sensor.Depending on the type of meter device utilized and on the type ofconsumable product/energy source, the data pulses and/or other signalindication may be converted to consumption (e.g. kWhr, Therm, Gallons,Lumens, etc.) on each measured supply feed or distribution service basedon a programmed conversion factor. The time rate of measuring andcollecting pulse data may be pre-programmed or adjusted based on suchfactors as the type of analysis to be done on the data, the bandwidthavailable to transfer the data from the meters to theserver/workstation, or the capability of the meters themselves. Thepulse data may be accompanied by meta-data, such as time stamps of whenthe pulses were measured. The data may further be protected with dataencryption and/or other security measures to ensure the integrity andprivacy of the data during transmission between the meters and theserver/workstation 127 and during access to the data once stored inserver/workstation 127. For example, the data may be encrypted and/oraccompanied by a digital signature to ensure that the meters may not bealtered or spoofed. An initial key exchange may occur between the metersthemselves and/or between the meters and/or the workstation. In thisway, once the meters are registered, the communications may not bespoofed and/or altered. Hence all reporting is done in a secure manner.Where time stamps are used, the time stamps may utilize any timebase/zone, such as GMT-0 such that collection of data may be timesynchronized with other measurements collected from the samedistribution system and/or facility, or from other distribution systemsand/or facilities.

Once collected, the server/workstation may compile the data from eachsensor/channel into time sequences of data. Exemplary data sequences maybe graphically illustrated either on the meter and/or on theserver/workstation 127 as, for example, illustrated in FIG. 2. Thisgraph may also be analyzed remotely on a laptop computer, across theInternet, and/or on a smartphone. Graph 200, for example is arepresentative plot of kilowatt-hours (kWhr) of electrical powermeasured by meter 104 in FIG. 1 over a period of a week. As can be seenin FIG. 2, in exemplary embodiments, power typically oscillates duringthe week, with peaks reached during typical business hours and droppingduring off hours and/or the weekend. Graph 200 may be variouslyconfigured including as a composite of smaller data sequences such assequences 201 and 202. A representative graph of what data sequence 202may look like is shown in more detail below the graph of data sequence200. As can be seen in the graph of sequence 202, more detailedsequences, such as sequence 203 may be extracted. The detailed datasequences associated with individual meters may help pinpoint potentialissues with the generation and/or use of a particular consumableresource.

FIG. 3 illustrates a process, according to some embodiments, to analyzethese data sequences to determine any deviations from an expected amountof power that is consumed and/or produced by one or more particularusers within a group of users connected to the measured service. Process300 starts at 301 where the supply of a consumable product is measuredin a distribution system by a meter (e.g. 104). The measured values arethen transmitted from the meter in step 302, and subsequently receivedby a processor (e.g. server/workstation 127) in step 303. Steps 301,302, and 303 may be accomplished as already described with respect toFIG. 1 and may result in one or more data sequences as illustrated inFIG. 2. Steps 301, 302, and 303 may occur on a pre-determined scheduledbasis, as a result of the processor requesting the measured data fromthe meters, or both. In step 304, signatures of users are retrieved froma database. Each signature is a characterization of the access to theconsumable product by one or more of the users. In step 305, theprocessor uses the signatures and the measured data sequences todetermine which of the group of users connected to the distributionservice is actually accessing the consumable product, and/or how much ofthe product is being accessed. Further, the consumable productsconsumption and/or generation from a plurality of facilities may beaggregated over time and/or over different facilities and used toformulate profile for a collection of assets. These profiles may then beused to negotiate with various suppliers of consumable products in thepurchase of the consumable product. For example, an individual buildingowner often lacks sufficient market power to negotiate efficiently.However, using embodiments tens, hundreds, thousands, ten thousand, andeven hundreds of thousands of facilities may be aggregated over thecontinent and over the world to negotiate the least expensive rates forconsumption of the consumable products and the most favorable offsetsfor sources of the consumable products. In this manner, embodiments mayallow the aggregation of many facilities to provide market power and totake advantage of the smart networks for consumables and the increasingderegulated environments for the delivery of consumables.

As an example of step 305, a processor in server/workstation 127 may usea pattern matching algorithm to match data sequence 203, illustrated inFIG. 2, to a signature which characterizes cell tower 116 in FIG. 1. Theprocessor may further use more than one signature or may combinesignatures to determine use of the resource by one or more users. Forexample, signatures for cell tower 116 and HVAC 119 may be combinedadditively to determine simultaneous use by 116 and 119. The processormay also manipulate the signatures and/or data sequence using varioussignal processing algorithms in the process of determining the users.For example, the processor may transform the signatures and datasequences from the time domain to the frequency domain using variousFourier transform algorithms. The processor may also use variousartificial intelligence/smart agent/learning algorithms to process thesignatures and data sequences either in the time domain and/or thefrequency domain. The algorithm may also smooth the uses by filteringthem with a high pass and/or low pass filter in order. In exemplaryembodiments, the use of filters allows the artificial intelligencealgorithms to operate more efficiently. For example, the processor maytrain a neural network on known operating conditions of various users,different combinations of signatures, and various data sequencesacquired during the known operating conditions (with or withoutfiltration) to develop a matching algorithm that is subsequently used inidentifying later aberrations from known usage patterns.

In one exemplary embodiment, an artificial intelligence engine mayimplement the following algorithms:

a. Average exceeding threshold by Standard Deviation

-   -   1. Sample 30 minutes data;    -   2. Determine if in occupied mode or unoccupied mode, determine        outside temperature;    -   3. Look at averages of sampled data to see if it exceeds the        previous average (threshold power) by a standard deviation        (either user selectable or automatically determined by past        experience;    -   4. In event the Threshold Power is exceeded, send email energy        alarm to network administrator and/or customer including, for        example, date, time and alarm type such as reading.

b. Determine Appropriate Start and Stop times

-   -   1. Monitor data points immediately following occupancy in the        Morning start up sequence including outdoor temperature;    -   2. As slope of kW line changes by an administrator configurable        amount in consecutive data points (including average time        windows), store the amount of change;    -   3. The result may be used to alert the building owner based on        the forecast of what time their building should start and        compare that to what time they have in their occupancy schedule.    -   4. Allows critical functions such as HVAC to be matched to        actual work schedules in building.

The Artificial Intelligence Engine may constantly search the utilitysignatures in the database to associate a signature to a hard asset. Forexample: a 50 HP Fan Motor with Variable Frequency Drive may have aparticular electrical consumption signature comprised of amps, powerfactor, watts. The AI engine may constantly review every librarysignature in the database (whether real or from a factory teststand—manufacturer's data) to correlate the motor signature to thelibrary via statistical analysis. The AI engine may determine acorrelation error factor between the motor signature and the librarysignatures (e.g. motor signature−library signature=error factor) viaheuristics, optimization, simulated annealing, beam search, randomoptimization and/or a custom AI algorithm. When the error factor isbelow an acceptable level, the AI engine may output the load associatedwith the library signature, i.e. the 50 KW fan motor with VariableFrequency Drive.

The AI engine may thus inform an operator what load to look for. The AIengine may also write to the facility automation system sending computercode (bacnet, lontalk, any communication protocol accepted by facilityautomation system) to shutdown the load (50 Hp motor in this case) basedon a permissive such as occupancy of facility, demand reduction, etc. Insimple terms, an exemplary embodiment captures a signature measured fromthe distribution system and compares the measured signature to thelibrary of signatures. The AI engine may search for Global Signaturessuch as for an entire facility or a sub-level within the facility (e.g.50 KW Motor in a HVAC Unit on Roof). The comparison may be used toisolate and identify potential loads. The potential loads may then becommunicated to an operator/customer or automatically controlled (e.g.on/off) via a communication protocol to regulate use of the distributedservice.

Returning now to FIG. 3, the sequence will be further explained. Afterstep 306, the processor (e.g. server/workstation 127) may then generatereports which detail the usage of the consumable product by varioususers and/or alerts when any user diverges from an expected usage. Thereport may be customized to detail access by a particular user over afixed duration, and/or may detail a group of users of a specific tenant.The processor may further determine costs of the access by theparticular user and/or group of users to the consumable product andinclude the cost in the report. For example, as in FIG. 1, theconsumable product may be a public utility such as electrical power.Cost may simply be based on a constant rate, or may be based on a tieredutility rate which accounts for different rates at different times (i.e.peak and non-peak usage times). The reports may also include usage of aconsumable product in graphical form, such as in FIG. 2. The report mayfurther include other secondary data that may be derived from theconsumable product usage. Exemplary secondary data may includecalculations of green house gas emissions by a particular user. Thesereports may be processed as bills and sent directly to the users as wellas copied to the building managers.

Process 300 may be performed by an autonomous processor that workscontinuously collecting data (e.g., pulse data) and determining usersand/or aberrations in real-time or near real-time, and generatingreports on a fixed schedule (i.e. monthly) or based on a certain levelof use or cost (or aberrations in use or cost) being reached by aparticular user or group of users. The reports may take the form of aninvoice and sent to tenants responsible for the particular usersdetailed in the report. These reports may be generated and sent in theform of hard-copies and mailed, in electronic form and sent viaelectronic mail, text message or other form of electronic transfer, orin the form of voice messages sent via phone line. Further embodimentsmay allow the reports, including billing information and graphical datato be displayed on any customer interface device; desktop, laptop, PDA,Blackberry and or client internet portal, and may be further providedthrough a website hosted by the processor. By serving the data from awebsite, a tenant/customer may be able to view usage and cost data andgraphic displays in real-time and/or near real-time. As referred herein,“real-time” refers to updating the usage data as it is collected andcalculated with little and/or relatively little delay other than thetime it takes to process the data. The amount of delay may be a designedlimit on processing time, such that the data may be used in closed loopcontrol of users, or the delay may simply be dependent on the resourcesavailable in measuring, transferring, and processing the data. For thepurposes of this application, “real-time” and “near real-time” refers tothe same concept in processing data.

Process 300 may be augmented with additional steps of process 400illustrated in FIG. 4, and described with respect to FIG. 5, forincorporating operating conditions into the determination of the varioususers. In this exemplary embodiment, Process 400 starts at 401 bymeasuring environmental conditions of areas which are proximate to aparticular user or are served by a particular user. For example, asillustrated in FIG. 5, HVAC 119 and lighting 120 may serve a room 500 inthe facility 101 of FIG. 1. Environmental conditions such as temperature503 inside of the room and temperature 502 outside of the room may bemeasured. Other operating conditions which affect usage of theconsumable product may also be captured, as in step 402 for example,where persons within room 500 may be counted by a sensor 504. Suchmeasurements of operating conditions may be accompanied by meta-datasuch as time stamps or time intervals such that the operating conditionsmay later be correlated to usage data of electrical power by users 119and 120. In step 403, the measured environmental and other capturedoperating conditions are transmitted to the processor. FIG. 5illustrates an exemplary data collection node 501 collecting themeasured values and transmitting them to the processor inserver/workstation 127 through cellular network 125. Data collectionnode 501, may be the same as meters 104 and 105, or may be some othercomputing platform operating in the same manner as 104 and 105 over thesame types of communication links to transfer data to server/workstation127. In step 404, the processor in server/workstation 127 receives thetransmitted data. In addition to receiving operating conditions measuredfrom the facility, the processor may retrieve other operating conditionsfrom a database such as in step 405. The processor, in step 405, mayretrieve facility characteristics from the database, such as squarefootage of rooms in the facility; age of the facility; insulationfactors of walls, windows, and other structures; load factors whichindicate peak usage versus minimal usage ratios, historical seasonalusage information, age and efficiencies of the users, etc. In step 406,the same steps as in steps 301 to 305 of process 300 are performedexcept that the operating conditions measured from the facility andretrieved from the database are incorporated in to the step 305 fordetermining access to the consumable product by a particular user. Instep 407, a report may be generated in the same manner as in step 306 ofprocess 300. The report may further include details of the operatingconditions acquired in steps 401 to 405, and other secondary data thatmay be derived from the operating conditions and consumable productusage. Exemplary secondary data may include calculations of green housegas emissions by a particular user.

As with process 300, the steps of process 400 may be performedautonomously, in which the operating conditions and usage data arecontinuously collected, users are determined in real-time or nearreal-time, and reports are generated on a fixed schedule (i.e. monthly)or when certain levels of usage or costs are reached by a particularuser or group of users.

In order to perform processes 300 and 400, the processor performing theprocess it may be desirable for the processor to have either preloadedand/or learned signatures of the various users connected to thedistribution system. In another exemplary embodiment, the processor maycreate these signatures according to a process 600 as illustrated inFIG. 6. In one exemplary embodiment, Process 600 in FIG. 6 starts bymeasuring access to a consumable product by a plurality of users on asupply feed or a distribution service over a fixed period of time.During the measuring, the operating states of the plurality of users arealso determined. The operating states may be determined by monitoringthe users or controlling the users. The monitoring and controlling maybe performed by the processor using the same or similar communicationlinks used for receiving data from meters. Other operating conditionsmay also be monitored or measured over the fixed period of time. Theoperating conditions may include the same measured (e.g. inside andoutside temperature, person count, etc.) and facility characteristics(e.g. square footage, facility age, insulation factors, load factors,historical seasonal usage information, age and efficiencies of theusers, etc.) as in process 400. Measuring access to the consumableproduct and monitoring the operating conditions may be achieved by thesame or similar manner as is accomplished in processes 300 and 400. Onceaccess to the consumable product and operating conditions are measuredor determined, the data is correlated to the known operating states todetermine the signatures which characterize the access by one or moreusers of the plurality of users. The signatures may contain variables toaccount for different operating conditions or may assume an average orestimated operating condition. Multiple signatures may further becreated for the same on or more users, with each signature reflecting adifferent set of operating conditions.

The creation of signatures may be accomplished by a variety of differentalgorithms. For example, referring back to FIG. 2, data sequence 203 mayhave been recorded when HVAC 119 was being cycled on and off, lighting112 was being powered during regular operating hours of the facility,and cell tower 116 was operating. A processor in server/workstation 127may use a pattern matching algorithm to correlate transitions in datasequence 203 to the changes in states of HVAC 119, lighting 112, andcell tower 116 to create signatures which characterize each of theseloads or a combination of these loads. Previously determined signatures(e.g. for lighting 112 and HVAC 119), may be used to cancel out theeffects of certain loads (e.g. lighting and HVAC) in determining asignature of just one of the users (e.g. cell tower). In this manner,the signature may be combinable or divisible to uniquely reflect use ofthe consumable product by a combination of users on a single supply feedor distribution service. The processor may also manipulate the datasequence and state information using various signal processingalgorithms in the process of determining the signatures. For example,the processor may transform the data sequences from the time domain tothe frequency domain using various Fourier transform algorithms. Theprocessor may also use various artificial intelligence/intelligentagents/learning algorithms to determine the signatures. For example, theprocessor may train a neural network on known operating conditions,operating states, and measured data sequences to determine thesequences. The signatures may take on a plurality of forms, including atime sequence of data or a frequency spectrum of data that may becombined with other signatures to be matched to measured data sequences.In the case of using a neural network to identify a user in process 300and 400, the signature may be in the form of branch weights in theneural network for identifying a particular combination of users.

After determining one or more signatures, the signatures may be storedin a database at step 604. In addition to storing the signatures, themeasured or determined operating conditions may also be stored to thedatabase in step 605. The signatures and operating conditions may bestored in a single database, or may be stored in separate and numerousdatabases. The databases may be collocated with the processor, or may beremote and accessed by the processor through a network connection.Process 600 may finish with generating a report of the stored signaturesand operating conditions. The databases may then be used, for example,in processes 300 and 400 for later determining access to the consumableproduct by a particular user. In the example of FIG. 1, the varioussignatures would reflect various electrical loads and sources as alreadydescribed. The database of signatures may also be used in otherprocesses such as determining energy ratings of users or compliance ofdifferent users and facilities with applicable governmental regulations,or trade group certifications.

In addition to determining energy usage by users within a facility,determining energy performance of the facility may also be used invarious embodiments. FIG. 8 illustrates a building envelope 800 of afacility in which energy performance may be determined. Buildingenvelope 800 may include the building structure, which thermallyseparates an enclosed volume from an outside environment. The structuremay include, for example, any combination of building material (e.g.,cement, glass, wood, metal, etc.), and may be used for any purpose(e.g., residential, commercial, industrial, etc.). For simplicity,building envelope may be shown schematically to include a solidperimeter with a single enclosed space, but the building envelope mayalso include floors, ceilings, and any other structure which enclosesthe volume of interior space.

Various aspects of building envelope 800 described herein may also applyequally to multi-room structures, a single room within a multi-roomstructure, a single floor within a multi-floor structure, structureswith openings such as doorways, vents, windows and other fenestration,structures with ceilings of various heights, structures with variousshaped perimeters, and/or structures with walls, floors, and ceilings ofdifferent shapes and sizes.

One function of building envelope 800 is to provide thermal isolationbetween an outside environment 809 and inside environment 808, such thatthe inside environment 808 may be controlled in an energy efficientmanner. Although, generally, the outside environment 809 comprises thespace outside of the entire building structure, outside environment 809may equally refer to one or more rooms or spaces within the buildingstructure bordering a building envelope which encloses only portion ofthe building structure and/or to adjacent buildings where, for example,the building abuts an adjacent building. The building envelope may, forexample, enclose a group of one or more rooms, or a single floor.

Determining energy efficiency of a building may include determining thethermal properties of the building envelope. In particular, where abuilding envelope has a thermal mass, the building may have severalcomponents of induced and residual heat flow through the buildingenvelope.

Thermal mass (e.g., heat capacity) may be considered to be the propertyof an object to store heat and may be measured in Joules per degreeCelsius (J/° C.), in British Thermal Units per degree Fahrenheit (BTU/°F.), and/or equivalent. The thermal mass of an object may depend on thespecific heat capacities of the materials making up the object. Specificheat capacity, denoted C, is often considered the materials heatcapacity per unit of the material, and may be specified per mass (e.g.,BTU/[° F.×[b_(m)]), and/or per volume (e.g., BTU/[° F.×ft³]). Denseobjects, such as brick and stone, typically have a greater capacity tostore heat than less dense objects, such as wood or foam insulation. Thebuilding envelope's thermal mass, M_(ENV), will be a function of thematerial making up the buildings structure.

In addition to the M_(ENV) of the building envelope, thermal mass mayalso be present within the inside environment, represented as object 801having thermal mass M_(I), and within the outside environment,represented by object 810 having a thermal mass M_(O). Objects 801 and810 may each represent a single object, or may each represent acomposite of the thermal masses of multiple objects. Inside object 801,for example, may include furniture, equipment, vehicles, people,warehoused goods, and other movable or permanently affixed structures.Outside object 810 may include other buildings, building structures,roadways, and other movable and affixed objects.

Various embodiments include determining heat flow through and/or intothe building envelope. FIG. 8 includes various illustrative examples ofheat flow shown as heat paths 802 to 807 having respective heat flowsQ_(ENV), Q_(EL), Q_(W), Q_(G), Q_(P), and Q_(HVAC). Heat flow is oftenthe quantity of heat energy transferred per unit of time (e.g., W=J/s,BTU/Hr). Related to heat flow, heat flux, denoted Q^(f), may be definedas the quantity of heat per cross-sectional unit area, and may bemeasured in watts per meter squared (W/m²), and/or other equivalentunits. The heat paths shown in FIG. 8 may move heat between the outsideenvironment 809 and the inside environment 808 and between theenvironments and the thermal masses M_(EV), M_(I) and M_(O). Variousembodiments include tracking of heat flow along the various inducedpaths periodically over time.

Heat path 803-807 often represent induced heat flow, and heat path 802often represents a residual heat flow. Induced heat flow may be theresult of supplying or injecting energy sources into the buildingenvelope, which may then produce heat through the sources consumption(i.e., a consumable product). Examples of energy sources includeelectricity, fossil fuels, and people. Induced heat flow may also resultby mechanical means, such as heating, ventilation, and air conditioning(HVAC) systems, which often mechanically move heat in or out thebuilding envelope to control the climate within the building envelope.

Heat path 803, Q_(EL), of FIG. 8, represents heat flow produced byelectrical power supplied to the building envelope. In various aspects,electrical power may be measured and/or its distribution monitored asdescribed with respect to FIG. 1 in order to determine heat producedfrom its use within the building envelope.

Referring back to FIG. 1, heat flow 803, Q_(EL), into the buildingenvelope may depend on the distribution and use of the electrical power.The distribution system itself, consisting of distribution point 106,and services 120-124, has electrical resistance and may have a powerloss in the form of heat according to the equation of P=I²*R, where P isthe power consumed, I is the current passing through any particularpath, and R is the resistance of the path. Heat may also be produced invarious forms by the end load. For example, lighting 107-112, mayproduce heat that is predominantly radiation heat, while computerequipment in computer server room 114 may heat the interior environmentpredominantly through conduction and convection. Other loads, such ascharging circuit 129 may not convert all of the electrical power intoheat, but may instead store the power in batteries, fuel cells, or otherstorage device. Still, other loads may convert some of the electricalpower into mechanical work.

In various aspects, heat flow 803, Q_(EL), is determined by measuringthe flow of electrical power through one or more meters and sub-meters,such as 102-105, and/or by monitoring one or more loads, such aslight/load meter 133 monitoring lighting 110. It should be noted thatthe various loads and distribution paths, such as HVACs 117-118, celltower 116 and portions of services 120-122, may be outside of thebuilding envelope, and thus, would not add heat within the buildingenvelope environment.

Heat path 804, Q_(W), in FIG. 8 may be another source of induced heatflow produced by the flow of water through the building envelope. Likeall matter, water has the ability to store heat, and has a heat capacityof 1 BTU/[° F.×]b_(m)] (approximately 4.2 J/(g*K)). As water flowsthrough a building envelope, the water may transfer heat to or from theinside environment and/or the thermal mass of the building envelope. Inmany situations, the amount of heat transfer from water may benegligible, but in various embodiments, water has a non-insignificanteffect. For example, in hotter climates, water which has been cooledthrough supply lines underground, may draw heat from the insideenvironment 808 as the water passes through pipes or through radiatorswithin the building. In other embodiments, hot water used to heatnumerous buildings in a campus system may be piped into a buildingenvelope and through radiators to dissipate the stored heat within thebuilding envelope. In yet other embodiments, water which has been heatedwithin the building envelope by heat produced from another energy sourcemay carry heat from the building envelope through drain pipes. Invarious embodiments, water flow and temperature may be monitored inand/or out of the building in order to calculate a heat flow 804, Q_(W),resulting from the water flow.

Heat path 805, Q_(G), in FIG. 8 provides another source of induced heatflow produced by the flow of fossil, bio, or synthetic fuels. The fuelmay be a gas, such as natural gas, biogas, propane, butane, etc., may beliquid, such as compressed natural gas, liquid propane, gasoline,kerosene, diesel, etc., or may be solid, for example coal, wood, etc.Like water, heat flow may result from the heat capacity of the fuelitself storing energy, transferring heat in or out of the buildingenvelope directly as a result of the fuel flow. Accordingly, in variousembodiments, temperature and fuel flow in and/or out of the building aremonitored by one or more meters to calculate a heat flow Q_(G) resultingfrom the heat capacity of the fuel.

Like electricity, the heat path 805, Q_(G), may also result from fuelflowing into the building environment, and then being consumed toproduce heat. For example, a building may have a natural gas utilitysupply used for water heating, furnaces, clothes dryers, cooking, andother various functions. The heat flow Q_(G) resulting from consumingthe fuel will depend on the quantity of fuel consumed and energyconversion efficiency of each particular application within the buildingenvelope. Accordingly, one embodiment monitors distribution of the fuelto various consumption points within the building envelope, anddetermines heat flow based on known, estimated, or measured energyconversion/efficiency factors. For example, natural gas has a knownenergy conversion factor through combustion (e.g., 1000 BTU/ft³). In acooking application using natural gas, one embodiment may monitor thequantity of gas consumed by a stove and use the known energy conversionfactor to determine heat transfer into the building envelope. In thesame system, exhaust vents over the stove may be monitored to determineair temperature and flow from the cooking area to determine heat flowleaving the building envelope through the exhaust. In variousembodiments, the heat path induced by the exhaust may be included in theheat flow calculation Q_(G), or may be calculated as a separate heatflow factor. The heat flow resulting from the exhaust would bedetermined in the same way as water based on flow rate, temperature, andheat capacity of the exhaust.

Heat path 806 having heat flow Q_(P) includes another source of inducedheat flow resulting from the moving of self contained heat emittingbodies being moved in and out of the building. The most typical selfcontained heat emitting bodies are people moving in and/or out of thebuilding. In various embodiments, doorways and other entrances to abuilding envelope are monitored to count people entering or exiting. Themonitoring may exist only for building entrances, or may occur perfloor, or per room. Each person's contribution to heat flow Q_(P) maythen be determined by estimating heat emission based on an averageperson. In another embodiment, heat emission estimates of each personmay be based on more detailed monitoring which determines size, heightand/or weight of persons entering and exiting the building, room, orfloor. In yet another embodiment, each person's heat emission may beestimated based on the amount of activity each person exerts, which maybe measured, for example, by using motion sensors. In yet anotherembodiment, thermal detectors or cameras may measure a person's heatsignature or heat output to determine that person's contribution toQ_(P).

Although Q_(P) is described with respect to people, the same embodimentsmay equally be applied to other illustrative self contained heatemitting bodies such other animals. In yet another embodiment, the selfcontained heat emitting bodies may include automobiles moving in and outof parking garages or other spaces within the building envelope. Inmonitoring the automobiles, various embodiments may treat theautomobile, drivers, and passengers as one heat emitting body, or maydistinguish each automobile, driver, and passenger as separate heatemitting bodies and/or based on the size and type of the automobile.

Heat path 807 having a heat flow Q_(HVAC) represents heat flow inducedby Heating, Ventilation, and Air Conditioning (HVAC) systems. HVACsystems, such as a heat pump, typically mechanically move heat in or outof the building envelope to control the climate inside the buildingenvelope. In various embodiments, an HVAC system may include electricheaters, natural gas furnaces, hot/chilled water circulation, or othersystems, which create heat paths that include previously described heatpaths, such as Q_(EL), Q_(W), or Q_(G). For example, an HVAC system withelectric heaters would generate heat directly from an electric utilityservice as described above with respect to Q_(EL). In these embodiments,the heat path may be considered as either Q_(HVAC) or as one of theother described heat flows. In other various embodiments having an HVACsystem such as an air conditioning system or a heat pump, electricity orother energy source may be converted into mechanical energy to create aseparate heat path which forces heat in or out of a building envelope.

In various embodiments, heat flow Q_(HVAC) may be determined by directlymonitoring input and/or outputs of the HVAC system. For example, in aforced air furnace, intake and outtake airflow, along with temperatureof the intake and outtake air may be measured with one or more meters tocalculate the heat output of the furnace. In other embodiments, theenergy source (e.g., electricity) supplying the HVAC system may bemonitored, and an estimated, measured, or manufacture suppliedconversion/efficiency factor may be applied to determine the heatmovement through the building envelope based on the measured energysource.

As shown in FIG. 8, in addition to the induced heat paths heat paths 803to 807 having respective heat flows Q_(EL), Q_(W), Q_(G), Q_(P), andQ_(HVAC), a building envelope may also have a residual net heat path 802having a heat flow Q_(ENV). Heat flow Q_(ENV), often depends on theinsulation properties of the building structure.

In a simple embodiment, heat path 802 may be predominantly throughconduction of the building envelope and can be characterized by acomposite thermal resistance, or R_(VALUE), of the material that makesup the building structure. R_(VALUE) for a particular material isdescribed by the equation R_(VALUE)=(T2-T1)/Q^(f), where T2-T1 is thedelta temperature on either side of the material and Q^(f) is the heatflux, or heat flow per unit area, through the material. R_(VALUE) formany materials is well known and provided by the manufacturer.

Often, the building structure may not be a single material, but acomposite of multiple materials in layers. For example, as shown in FIG.14, a cross-sectional view of a building wall 1400 may include anoutside concrete layer 1401, next to a thin air layer 1402, followed bya sheathing layer 1403, an insulation layer 1404, and a drywall layer1405. In this example a composite R_(VALUE) would be calculated asR_(VALUE)=R_(VALUE(CONCRETE))+R_(VALUE(AIR))+R_(VALUE(SHEATHING))+R_(VALUE(INSULATION))+R_(VALUE(DRYWALL)).In practice, wall construction is typically more complicated and mayinclude many more parts such as wooden or metal studs, epoxies, nails,pipes, etc. To determine R_(VALUE) of complicated wall assemblies, aweighted average of each R_(VALUE) of each material may be used, or thecomposite R_(VALUE) may be computed using modeling software of the wallassembly.

In many buildings, R_(VALUE), based on conduction alone is insufficientsince many more factors contribute to the residual thermal path 802.Radiation and convection from the atmosphere also play a role, as wellas air infiltration through doorways, windows, vents, and cracks. FIG. 9illustrates the building envelope of FIG. 8, but replaces thermal path802 with a more comprehensive illustration of residual thermal paths 901to 909. In FIG. 9, thermal path 901 having heat flow Q_(CDN) representsthe conduction thermal path previously discussed. Heat flow Q_(CDN) willdepend on R_(ENV), the R_(VALUE) of the building envelope, and on thetemperatures T_(ENVI) and T_(ENVO), which often are the inside andoutside surface temperatures 910 and 915 respectively of the buildingenvelope. T_(ENVI) and T_(ENVO), in turn, may be determined by heattransfer from the inside and outside environments 808 and 809, throughradiation, conduction and convection.

In the outside environment, radiation from the sun, represented byQ_(RAD) may be determined predominantly by the sun position,obstructions which block the sun, atmospheric conditions such ascloudiness and green house effects, and reflectivity of the buildingsurface. Time 920 and Date 921 may be used to determine sun position.Weather forecasts and models may be used, or direct measurements may bemade at various locations on the outside of the building envelope, todetermine atmospheric conditions such as brightness 916. From thesefactors, radiation hitting the building envelope may be determined. Thedetermined radiation along with the known reflectivity of the surfacemay then be used to determine heat energy transferred to the outsidesurface and/or the lower temperature space or zone.

In addition to outside radiation, heating of the building envelope'soutside surface occurs through conduction 903 and convection 902 havingheat flow Q_(CDN) and Q_(CVN), respectively. Heat transfer throughconduction can be determined by the difference between the airtemperature 919 and building surface temperature 915 having temperaturesT_(AIRO) and T_(ENVO) respectively, and the respective thermal masses(i.e., heat capacities) of the air and building envelope. The thermalmass of the air may vary with humidity 918 (H_(O)) and barometricpressure 922 (P_(O)). Heat transfer through convection 902 is affectedby the same factors as conduction path 903, but may further be affectedby atmospheric conditions such as wind 917 (W_(O)).

In the same ways that heat is transferred from the outside environmentto the outside surface of the building envelope, heat may be transferredfrom the inside surface of the building envelope to the insideenvironment through radiation heat path 909, conduction heat path 908and convection heat path 907.

Radiation may also enter the building envelope directly through heatpath 905, Q_(RAD), which may comprise openings such as doorways,windows, and/or other fenestration. Open doorways would provide noresistance to radiation entering, whereas windows will typically have adesigned emissivity (e) which is a measure of the amount of radiationreflected, and thus prevented from entering the building envelope.

Building envelope may also have a residual heat path 906, Q_(INF),resulting from air infiltration through openings in the buildingenvelope. Heat path 906 has a representative thermal flow Q_(INF), whichmay be determined by the cross section and positions of openings, andenvironmental factors such as outside wind W_(O), inside and/or outsidehumidity, 918 (H_(O)) and 912 (H_(I)) respectively, and/or inside and/oroutside barometric pressures, 922 (P_(O)) and 923 (P_(I)) respectively.

Building envelopes are generally designed to minimize the thermal paths901-909 shown in FIG. 9. As previously discussed, as-built structuresmay not and often do not meet the insulation performance of a planneddesign after completion. Errors in the designed thermal performance maybe caused by design variations that are not reflected in a model,construction of the structure which is not to specification, incorrectassumptions on building usage and weather, utility equipment which isnot installed correctly or functioning according to specification,insufficient model fidelity, and numerous other factors. Further, abuilding's energy performance may change over time due to the aging ofmaterials, modifications to building structures and systems, or damageto the structures.

In addition, thermal mass M_(ENV) of the building envelope may impactthe thermal performance of the building envelope by serving as a heatreservoir for some of the conducted heat through the building envelope,thereby damping or adding a time delay to the conducted heat transferbetween the inside and outside environments. Likewise internal object801 and external object 810 may have the same effect in dampeningvariations in the inside and outside temperatures 911 and 919respectively. For example, a house in the countryside will be in thepresence of a vastly different outside thermal mass than that of anoffice building within a heat island of a dense city, and thus theoutside temperature of the building in the city may be higher. Further,objects 801 and 810 may be moved, or new objects erected, such asconstructing new adjacent buildings. Because objects 801 and 810 may bemoved or erected, their thermal impact on building envelope 800 maychange over time.

Because of errors in the designed thermal performance and the change inperformance over time, various embodiments may periodically determinethe actual residual heat flow through the building envelope. In oneembodiment, heat flow and thermal performance of a building envelope aredetermined by process 1000 as shown in FIG. 10. In step 1001, inducedthermal paths 803-807 are determined as discussed above throughmonitoring and measurement of the various energy sources entering andleaving the building envelope. In step 1002, resultant induced thermalflows Q_(EL), Q_(W), Q_(G), Q_(P), and Q_(HVAC) are calculated asdisclosed above. In step 1003, the inside and outside environments aremeasured. The measurements may occur periodically at fixed timeintervals, may occur in real-time, and may all be synchronized with eachother, and with the measurements of the induced heat flows.

In step 1004, residual heat flow is determined from the determinedinduced thermal flows and by measuring a change in the internal andexternal environments. For example if the internal environment staysstatic (e.g., temperature, pressure, and humidity do not change), thanthe residual heat flow may be determined asQ_(ENV)=Q_(HVAC)−Q_(EL)−Q_(W)−Q_(G)−Q_(P). In other embodiments,residual heat flow Q_(ENV) may be determined by taking intoconsideration the induced heat flows combined with changes in theinternal environment (T_(ENVI), P_(I), and H_(I)), changes intemperature of internal object 801, and/or changes in temperature of thestructure of building envelope 800.

Based on the determined residual thermal flow Q_(ENV), and the measuredenvironments, the actual thermal performance of the building envelopemay be determined in step 1005. The actual thermal performance can becalculated as a composite thermal resistance factor, R_(C), which notonly includes an R_(VALUE) characterizing conduction, but alsoincorporates the other residual thermal paths discussed above due toradiation, convection, and infiltration. In various embodiments,measured R_(C) may thus be a real-time function of the measuredenvironmental variables. In other embodiments a single R_(C) value maybe determined from the measured parameters, as a value defined over anaverage period, and/or at predefined environmental conditions. Invarious embodiments, the measured R_(C) function or single R_(C) valuemay be specified in construction or sales contracts, as a design metricor contractual obligation to meet by one party to the contract.

In step 1006, an error may be quantified between the measured R_(C) anda modeled R_(C) based on a modeled design. In step 1007, a source of theerror may be determined based on the type of error found. For example,if the quantified error indicates that thermal conduction was a primaryfactor in the error, than a builder may conclude that a wall was notassembled according to specification.

In step 1008, reports may be generated which detail the errors. Thereports may be provided at the conclusion of construction of thebuilding, periodically during operation of the building to stakeholders,such as owners, building managers, and leaseholders, or provided in realtime through, for example, web applications and analytical engines,which may continually calculate and display R_(C) which may vary basedon changing conditions.

In various embodiments, process 1000 may be performed in a staticmanner, such that one or more of the induced thermal paths may beinhibited. While inhibited, step 1003 may be performed to determineresidual heat flow by measuring over time, the inside environment and/orbuilding envelope temperature approaching equilibrium with the outsideenvironment. For example, electric, gas, and water utilities may be cutoff from the building, and all ventilation from an HVAC system shut.Once induced heat flow is inhibited, various environmental conditionsmay be monitored over time, such as T_(AIRI), H_(I), B_(I), P_(I),T_(ENVI), T_(AIRO), H_(O), B_(O), P_(O), T_(ENVO), W_(O), Time, Date,temperature of the envelope, temperature of inside objects, and/ortemperature of outside objects. Where no thermal paths are induced, anyheat transfer is typically residual. R_(C) may then be determined as afunction of time during which the two environments approach equilibriumwith each other. In one embodiment, the observation of the measuredenvironment may occur over a limited specific interval after the inducedheat paths have been shut off. The change in temperature between theinside and outside temperatures over the fixed interval may be specifiedas the thermal resistance factor, R_(C). Alternatively, the maximumamount of time for the inside environment to reach equilibrium with theoutside environment may be measured within a predetermined threshold.The maximum amount of time to reach equilibrium under the specificconditions may be specified as the thermal resistance factor, R_(C). Ineither case, specific initial outside and inside temperatures or otherenvironment variables may be specified.

In other various embodiments, process 1000 may be performed in a dynamicmanner, where changes in the induced thermal paths are measured andtracked over time. For example, heat flow from occupants may be trackedin real time so that R_(C) may be determined under conditions in whichthe building is often used. In another example, heat flow in a hotel maybe tracked in which occupants, electricity, gas, and water aremonitored. Determining heat flow through process 1000 may show thatexcessive heat from shower and/or laundry waste water is being lost fromthe building envelope. In this sense, process 1000 may be used not onlyas an audit of the residual thermal performance of the buildingenvelope, but also as an audit of unintended induced heat paths such asdrain water. Process 1000, in one embodiment may thus be used todetermine how both residual and induced heat paths may be improved.

In both static and dynamic embodiments, process 1000 may be repeatedcontinuously at periodic intervals (e.g., weeks, days, years, months,etc.) through loop 1011 in order to track changes in the thermalperformance of a building envelope over time. Changes may be the resultof aging of materials, defects in materials, modifications to buildingstructures and systems, or damage to the structures. Changes may alsoresult from changes in the environment (e.g., seasonal changes, solarcycles), or may result from changes in the building envelop and adjacentstructures (e.g., new adjacent buildings, changes in occupancy,remodeling, etc.).

In both static and dynamic embodiments, process 1000 may also be appliedat different stages of construction of the building envelope. Forexample, process 1000 may be performed when the outer layer (e.g.,brick, concrete) has been completed, but interior build out has not yetbeen completed. In this way, thermal performance (e.g., thermalresistance and thermal mass) may be evaluated for different componentsand layers of the building envelope.

In either the static and dynamic embodiments for determining R_(C),thermal mass of M_(ENV) and M_(I) may also be determined in step 1009 bymonitoring the rise in temperature of building envelope 800 and object801, and by monitoring any delay in the conductance of heat through fromthe inside environment and outside environment. For example, using themethods discussed above, induced and residual heat flow may be measuredover a fixed period of time and integrated to determine the total amountof heat energy flowing into and out of the building envelope. Acomposite thermal mass of the building structure, M_(ENV) or M_(I) (or acomposite of the two) may be determined as the difference between theheat flow in and out of the building per degree temperature change ofthe building structure over the measuring period. We note here thatM_(ENV) or M_(I), may not be thermal mass in strict definition of theterm since the temperature of the building structure may vary fromlocation to location within the building envelope. Accordingly, invarious embodiments, we use a thermal mass factor M_(C), which may bebased on estimates or averages of heat flow and temperature changes. Inone example, M_(C) may be defined in terms of energy storage of thebuilding envelope with respect to a change in the inside environmenttemperature (i.e., A T_(AIRI)) at equilibrium, given otherwise staticenvironmental conditions.

We have simplified the calculation of the thermal mass M_(ENV), andthermal mass factor M_(C), however in some embodiments a morecomplicated measure the building ability to store energy. For example,heat flow Q_(W) may be more efficiently transferred to the thermal massM_(ENV) than heat flow Q_(G). Therefore, in certain embodiments, thethermal mass M_(ENV), and thermal mass factor M_(C) may be employedwhich is based on the building envelope's energy storage propertiesacross different environmental conditions, with the different types ofheat flows.

The determined thermal resistance factor R_(C) and thermal mass factorM_(C) may be applied in various applications in step 1010. In thevarious applications of step 1010, a one-time measurement of R_(C)and/or M_(C), a periodically/continuously measured R_(C) and/or M_(C),and/or measured changes in R_(C) and/or M_(C) over time may be applied.In one illustrative application, the method of measuring R_(C) and/orM_(C) and a specific measured R_(C) and/or M_(C) may be specified inconstruction or sales contracts as a performance metric. Specificdamages may further be specified in the contracts based on R_(C) and/orM_(C). For example, the contract may specify how to calculate a monetaryloss in heating or cooling a building based on the delta between aspecified R_(C) and/or M_(C) in the contract and a measured R_(C) and/orM_(C). In some variations, specified, forecast, or measuredenvironmental variables may further be considered in determining themonetary loss. In another illustrative application, the specific methodsfor determining R_(C) and/or M_(C) may be used as industry standards tocompare different structures, or to establish minimum build criteria.

In another variation, resistance factors R_(C) and thermal mass factorsM_(C) may be collected from a number of buildings may be posted on awebsite or provided in a publication for providing comparativeperformance data between buildings. The data may provide R_(C) and/orM_(C) or some performance metric derived from these factors, and mayorganize the data in a manner to rank the building in order ofperformance. The builders of the buildings may be ranked in a similarmanner based on the buildings they construct. The builder's performancemay be based on one building or a number of building the builder hasconstructed. In this manner, historical R_(C) and M_(C) data may be usedfor certification purposes of different builders.

In another illustrative embodiment of step 1010, R_(C) and/or M_(C) maybe periodically tracked in real-time and used in a closed loop systemfor autonomously controlling a climate control system (e.g., HVAC) ofthe building. The periodically tracked R_(C) and/or M_(C) may be used inconjunction with measured or forecasted environment conditions, and/orin conjunction with varying cost rates of energy source to control theclimate control system. For example, on a night during off-peak ratesfor electricity, when cold whether is forecast for the next day, theinside environment may be pre-heated such that energy is stored in thethermal masses of the inside object 801 and the building envelope 800for later dissipation into the inside environment during the day whenthe building is being occupied and when electricity is at its peak rate.In this example, the determined R_(C) and M_(C) may be used to determinethe amount, duration, and time to pre-heat the building in order tooptimize cost savings. Because R_(C) and M_(C), energy rates, andthermal mass inside the building envelope may change over time, theoptimum parameters for pre-heating may change as well. R_(C) and/orM_(C) may be applied to pre-cooling as well. The determined R_(C) and/orM_(C) may show that no cost savings could be achieved because thethermal insulation of the building envelope is insufficient to retainheat for a required amount of time.

In various aspects, dynamically determining R_(C) and M_(C) may providea means for managing use of the building. For example, R_(C) and/orM_(C) may be determined on a room by room basis, and show that someareas of the building are inefficient to heat or cool. Building use maybe adapted such the spaces with poor R_(C) and M_(C) may be used forstorage or other purpose where climate control is less important.

Referring to FIG. 1, to perform the steps of process 1000, the inducedheat paths may be monitored. Using the electrical heat path as anexample, distribution systems may be designed to support specific users,and/or specific tenants of the facility. The design of the distributionsystem may provide individual tenants and individual employees of thetenant their own supply feed, distribution service, and/or differentcombinations thereof such that use and/or generation of an energy sourceby the individual tenant/employee may be uniquely measured using a meteron the tenant's/employee's supply feed or using a sub-meter on thetenant's distribution service. In various aspects, such monitoring ofindividual tenants or portions of the facility may be used to determineinduced heat flow for building envelopes enclosing only a portion withinthe overall building. In various embodiments, induced heat flow may bemonitored on a per tenant basis. For example one tenant may have severalmore occupants (e.g., self contained heat emitting bodies), and thusinduce greater heat flow. Lease rates may be proportioned betweentenants based on the relative induced heat flows.

In various embodiments, meter 104, sub-meter 105, and light/load meter133, may be added to a supply feed, distribution service, or particularload respectively, to measure and record supply and consumption of theenergy source over time. From these measurements, analysis may beperformed according to certain embodiments to determine the induced heatflow for the building envelope of the entire building or for a smallervolume within the overall building.

Meter 104, sub-meter 105, and sensor 133 may be variously configured. Inone embodiment, meters 104, 105, and 133 may include one or moresensors. Various sensors appropriate for measuring the consumptionand/or supply of the energy source will differ depending on the energysource being measured. As previously discussed, in the electricaldistribution system in system 100, the sensor may be an inductivelycoupled transformer, a current shunt, or other appropriate sensor formeasuring power, electrical current and/or voltage. In otherdistribution systems for other energy sources such as natural gas andwater, appropriate flow meters may be used. For people or automobiles,thermal sensors, thermal imaging systems, imagers, etc. may be used.While meters 104, 105, and 133 are described with respect to electricalpower, the various embodiments including the collection and processingof data will be the same regardless of the energy source.

As previously described with respect to meters 104 and 105, sensor 133may further include a computing platform to operate the sensor, andaccumulate pulse inputs (periodic measurements) from the meters andsensors. Meter 133 may include several sensors and accumulate data fromseveral different paths in the distribution system. As an example, meter133 may include a circuit board with 10 sensor channels for sensorswhich may each collect pulse data in parallel. A processor on thecircuit board may read each channel and accumulate data in the sameand/or separate memory devices (e.g. registers) for each channel. Themeter 133 may further have a data display which scrolls periodicallyand/or continuously to illustrate the pulses per channel. In addition tothe data display, meter 133 may have buttons or other inputs, which canbe used for on-site programming and/or trouble shooting. After on-siteprogramming/trouble shooting, further programming may be from a remotelocation and/or computer.

In various aspects, sensor 133 may transmit data to a server/workstationor other computing device as previously described with respect to meters104 and 105. Once collected, the server/workstation may compile the datafrom each sensor/channel into time sequences of data. The detailed datasequences and graphs associated with individual meters may help pinpointparticular induced thermal paths.

FIG. 11 illustrates a process, according to some embodiments, to analyzedata sequences to determine induced heat flow from various energysources. Process 1100 starts at 1101 where the supply of an energysource is measured in a distribution system by a meter (e.g. 104). Themeasured values may then be transmitted from the meter in step 1102, andsubsequently received by a processor (e.g. server/workstation 127) instep 1103. Steps 1101, 1102, and 1103 may be accomplished as alreadydescribed with respect to FIG. 1 and may result in one or more datasequences. Steps 1101, 1102, and 1103 may occur on a pre-determinedscheduled basis, as a result of the processor requesting the measureddata from the meters, or both. In step 1104, conversion factors of theenergy supply to heat production are retrieved from a database. Eachconversion factor is a characterization of a loads production of heatfrom consumption of the energy source. In step 1105, the processor usesthe conversion factors and the measured data sequences to determine theinduced heat flow through the building envelope. These values may thenbe used in step 1002 of process 1000.

Process 1100 may be augmented with additional steps of process 1200illustrated in FIG. 12, and described with respect to FIG. 13, formeasuring environmental conditions and self-contained heat emittingbodies. In this illustrative embodiment, process 1200 starts at 1201 bymeasuring the environmental conditions illustrated in FIG. 9. Forexample, as illustrated in FIG. 13, instruments 1303 may be used tomeasure inside environmental conditions such as such as T_(ENVI), P_(I),and H_(I), and instruments 1302 may be used to measure outsideenvironmental conditions such as T_(AIRO), H_(O), B_(O), P_(O),T_(ENVO), and W_(O). Step 1201 may also include acquiring environmentalconditions, weather forecasts and/or other data such as heating andcooling degree day forecasts and utility rate data from external sourcessuch as web servers which compile and distribute such data.

Other operating conditions such as the presence or heat emission of aself contained heat emitting body may be monitored in step 1202. In step1202, self contained heat emitting bodies 1305 to 1308 within room 1300may be counted by a sensor 1304. Alternatively, heat signatures of theheat emitting bodies may be detected using thermal imaging device 1309.These sensors may monitor self contained heat emitting bodies as theyenter and leave the building, and/or as they move from room to roomwithin the building. FIG. 13 illustrates the heat emitting bodies aspeople, but the bodies could equally be another animal, an automobile,and/or other object that emits heat generated from internally storedenergy.

In various embodiments, instruments 1302 and 1303 may include installedwired and/or wireless temperature transmitters (Infrared, RTD,thermistors, or any temperature measurement platform) on the inside,outside and within the building structure forming the building envelope.These sensors may be arranged in a matrix format and/or may be arrangedto measure temperatures at particular points of interest. FIG. 9 detailsillustrative aspects of temperature instruments within 1302 and 1303.

In FIG. 14, wall 1400 is illustrated with four layers 1401-1405. Aspreviously described, wall 1400 may include an outside concrete layer1401, next to a thin air layer 1402, followed by a sheathing layer 1403,an insulation layer 1404, and a drywall layer 1405. In variousembodiments represented by temperature instrument 1406, temperaturesensors may be placed between each material layer making up a wall orenclosure. Temperature instrument 1406 may for example consist of sixtemperature sensors with each sensor embedded between each of layer asshown (dotted bubble provided for clarity). The sensors are coupled bywires or wireless transmitters through the layers to a measurementdevice 1407, which may be located on either side of the wall. Withtemperature instrument 1406 temperature may be detected at multipledepths in the wall simultaneously, periodically, and in real-time.Instrument 1407 may measure temperature data from the sensorsperiodically and relay the data as discussed with respect to FIGS. 4 and12.

The sensors of temperature sensor 1406 may be installed duringinstallation of the material layers, or the sensors may be installed bythe material manufacture as an integral part of the material layers. Forexample, in one embodiment a manufacture of rolled fiberglassinsulation, may imbed a string of wired sensors spaced and taped alongthe paper backing of the insulation roll.

In another illustrative embodiment of a temperature instrument, atemperature detection probe 1408 having the ability to measuretemperature along incremental distances of the probe is inserted throughthe multiple layers of the wall. The probe may be a thin cylindrical (orother shape) rod which is inserted into a hole drilled or built into thewall. With the probe, temperature may be detected at multiple depths inthe wall simultaneously, periodically, and in real-time. Instrument 1407may measure or receive temperature data from probe 1408 via wired orwireless connection and periodically relay the data as discussed withrespect to FIGS. 4 and 12.

Using the illustrative temperature instruments 1406, 1408, or othersimilar instrument, a gradient of temperature can thus be detectedthrough the wall, and a more detailed view of the wall's thermalresistance (R_(VALUE)), thermal mass (M), thermal resistance factor(R_(C)), and thermal mass factor (M_(C)) can be determined. In otheraspects, instruments 1302 and 1303 may be used during the constructionof the building envelope to determine the wall's thermal resistance(R_(VALUE)), thermal mass (M), thermal resistance factor (R_(C)) andthermal mass factor (M_(C)). For example, a thermal imaging camera maybe used during the construction of a wall. As each layer of a wall isassembled, the thermal surface temperatures of the wall may be measuredusing the thermal imaging camera, or other thermal sensor. In this way,the contribution of each layer to the walls thermal resistance, thermalmass, or the thermal resistance factor may be independently verified.This may provide an advantage, for example, in detecting faulty orincorrectly installed material before the entire wall is assembled. As afurther advantage of measuring each layers contribution, either beforeor during the completion of the wall, these embodiments are able topinpoint the cause or causes of under or over thermal performance by aparticular component of the construction.

The measurements obtained in process 1200 may be accompanied bymeta-data such as time stamps or time intervals such that the operatingconditions may later be correlated to data captured in processes 1000and 1100. In step 1203, the measured environmental and other capturedoperating conditions are transmitted to the processor. FIG. 13illustrates an exemplary data collection node 1301 collecting themeasured values and transmitting them to the processor inserver/workstation 127 through network 125/126, which may be the same asthe communication paths describe with respect to FIG. 1, or which maydifferent than, but of the same types as those of FIG. 1. Datacollection node 1301, may be the same as meters 104, 105, and 133, ormay be some other computing platform operating in the same manner as104, 105, and 133 over the same types of communication links to transferdata to server/workstation 127. Server workstation 127 may be remotelylocated, or may be located within the building envelope. In step 1204,the processor in server/workstation 127 receives the transmitted data.The data may then be used in steps 1003 and 1004 of process 1000.

Returning to FIG. 14, plot 1409 illustrates the output of temperaturesensors measured over time. Each of the plot line 1410-1415 representstemperature measured by the sensors on each surface of layers 1401-1405.The distance between each plot line represents the temperaturedifference through a layer. As is shown, the temperature differencethrough each layer may vary over time at different rates and magnitudesthan other adjacent layers, depending on that layers thermal resistanceand thermal mass. Using the plots, the thermal resistance and thermalmass may be determined from the plots in the same manner as previouslydiscussed with respect to a single object.

Processes 1000, 1100, and 1200 may be performed by an autonomousprocessor that works continuously collecting data (e.g., pulse data),and determining R_(C) and induced and residual heat flow in real-time ornear real-time, and generating reports on a fixed schedule (i.e. daily).These reports may be generated in the form of hard-copies and mailed, inelectronic form and sent via electronic mail, text message or other formof electronic transfer, or in the form of voice messages sent via aphone line. Further embodiments may allow the reports, including billinginformation and graphical data to be displayed on any customer interfacedevice, desktop, laptop, PDA, Blackberry and or client internet portal,and may be further provided through a website hosted by the processor.By serving the data from a website, an interested party may be able toview usage and cost data and graphic displays in real-time and/or nearreal-time. As referred herein, “real-time” refers to updating the usagedata as it is collected and calculated with little and/or relativelylittle delay other than the time it takes to process and/or transmit thedata. The amount of delay may be a designed limit on processing time,such that the data may be used in closed loop control such as for use incontrolling a climate control system. The delay may also simply bedependent on the resources available in measuring, transferring, andprocessing the data. For the purposes of this application, “real-time”and “near real-time” refers to the same concept in processing data.

FIG. 7 is a block diagram of an exemplary computing platform 700 ofvarious embodiments, including an autonomous processor, meters,sub-meters, communication devices, and other equipment for performingthe various described processes. The various embodiments may beimplemented as one computing platform or multiple computing platforms,operating independently, or in a coordinated manner, such as in acomputer cluster. Using multiple computing platforms may provideredundancy, increased analysis and/or data storage, expanded capabilityto operate more users and/or geographically disperse users andconsumable products, and other advantages.

A processor 701 is configured to perform the various operations ofsystem control, telemetry sensing and gathering, data reception andtransmission, sensor calibration and control, consumable product sourceand load control, telemetry processing. Processor 701 may implement thevarious algorithms and processes as described herein, includingdetermining heat flow, thermal resistance factors, and thermal massfactors, producing secondary data products such as usage determinationsand reports, determining signatures of users and occupants, anddetermining specific user access to consumable products/energy sources.The algorithms implemented by processor 701 may include pattern matchingalgorithms, signal processing algorithms, and artificial intelligencealgorithms such as neural networks. Processor 701 may further controlthe operation of other components of computing platform 700 or maycontrol other remote equipment. Processor 701 may include one or moremicroprocessors, application specific integrated circuits, fieldprogrammable gate arrays, programmable interconnect and combinationsthereof. Processor 701 may be configured to communicate with andcontrols the various components within 700 over one or more buses.

In at least some embodiments, processor 701 carries out operationsdescribed herein according to machine readable instructions (e.g.software, firmware, hardware configuration files, etc.) stored in memory702 and/or 703 and/or stored as hardwired logic gates within processor701. Memory 702 and 703 may further store one or more databases whichmay be used to store energy conversion factors, occupant heatsignatures, consumption signatures of various consumable product users,sensor telemetry, calibration information, control information forvarious sensors, actuators, and other system components, costinginformation of various energy sources/consumable products, environmentalinformation, facility information, and other operating conditions. Thevarious databases may permit access by one or more processors in 701 orone or more other processing platforms 700. The various databases may beorganized to include meta-data for the various contents to enableselective retrieval of data to enable the processing as describedherein. As one example meta-data may be added to consumption data suchthat it is retrievable from the database in the correct time order, orsuch that signatures and data specific to certain tenants or areas ofthe building are provided from the database as a group of data that iseasily combinable.

Memory 702 and 703 may include volatile and non-volatile memory and mayinclude any of various types of storage technology, including one ormore of the following types of storage devices: read only memory (ROM)modules, random access memory (RAM) modules, magnetic tape, magneticdiscs (e.g., a fixed hard disk drive or a removable floppy disk),optical disk (e.g., a CD-ROM disc, a CD-RW disc, a DVD disc), flashmemory, and EEPROM memory.

Main processor 701 may be configured to communicate with other computingsystems, meters, sub-meters, etc. through various interfaces such aswireless interfaces that may include additional hardware and/orfirmware. Such interfaces may include one or more USB interfaces 708,Firewire interfaces 709, CAN protocol or other standard sensorinterfaces 710, other serial or parallel data interfaces 711, and/or oneor more wired and/or wireless network interfaces 712, 713. For example,communication to remote hardware may be accomplished through publicand/or private networks using network interfaces such as wirelessinterfaces 712, wired interfaces 713, combinations of such interfacesand other equipment. For example, wireless interface 712 may be a localWi-Fi interface connected through a modem of a land line DSL, Coax, orFiber-optic service provider network which connects to the Internet.Alternatively, wireless interface 712 may be equipment for connecting toa satellite or a cellular network as commonly used for cell phones,pagers, security systems, and personal digital assistants (PDAs).

For human interaction with the system, computing platform 700 mayinclude a display for presenting a graphical user interface, graphs,charts, configuration information, or other data relating to theembodiments described herein. Computing platform 700 may further includea console 705 for human interaction and control of the variousembodiments, and a printer 714 or other output device for generatingrecords such as invoices and usage reports. Such consoles may includekeyboards, mice or other input output devices. The display, console, andprinter may be co-located with the other components of 700, or may beremote from 700. For example, several of the components of 700 mayoperate as a server that is remotely accessed over the Internet orprivate network and which may provide web pages for presenting andinteracting with the system.

Computing platform 700 may further include other equipment such as powersupply 706, battery backups, fuses or other circuit protection features,finger print readers and other security devices, expansion slots foradditional hardware, audio equipment, infrared ports, etc.

The foregoing description is not intended to be exhaustive or to limitembodiments of the present invention to the precise form disclosed, andmodifications and variations are possible in light of the aboveteachings or may be acquired from practice of various embodiments. Theembodiments discussed herein were chosen and described in order toexplain the principles and the nature of various embodiments and theirpractical application to enable one skilled in the art to utilize thepresent invention in various embodiments and with various modificationsas are suited to the particular use contemplated. The features of theembodiments described herein may be combined in all possiblecombinations of methods, apparatuses, modules, systems, andmachine-readable storage memory. Any and all permutations of featuresfrom the above-described embodiments are within the scope of theinvention. For example, in performing processes 300, 400, 600, 1000,1100, and 1200, the various computing platforms performing the processesmay perform the various steps in a different order, may combine certainsteps from the different processes, or may omit certain steps.

Further, the various embodiments have been described in the context ofpublic utilities such as electricity and gas, and in the context ofhuman occupation. Such embodiments are exemplary only and the principlesdescribed herein are equally applicable to other energy sources wherethe distribution to multiple buildings may be measured and analyzed.Other example include distribution of compressed air, inert gases,steam, ice, dry ice, agricultural irrigation, livestock, domesticanimals, geothermal, nuclear, biofuels, biomass, and any other energysource.

1. A method comprising: receiving, with an automated data collectionprocessor, measurements of inside and outside environments of a buildingenvelope, and measurements of one or more measured energy sourcessupplied through a building envelope; and determining with theprocessor: an induced heat flow through the building envelope producedby the one or more measured energy sources, a residual heat flow throughthe building envelope based on the induced heat flow and changes in theinside and the outside environments, and a thermal resistance of thebuilding envelope based on the calculated residual heat flow and thechanges between the inside and the outside environments.
 2. The methodof claim 1, wherein the automated processor calculates the thermalresistance as a time function of the inside and outside environmentsapproaching equilibrium, while the one or more measured energy sourceshave been inhibited from entering the building envelope.
 3. The methodof claim 2, wherein the thermal resistance is based on the inside andoutside environments measured until the inside environment reachesequilibrium with the outside environment.
 4. The method of claim 2,further including: determining a thermal mass within the buildingenvelope.
 5. The method of claim 2, further comprising: including withina construction contract, a requirement that the building envelope meet arequired thermal resistance which meets the determined thermalresistance.
 6. The method of claim 5, further comprising: includingwithin the construction contract, a requirement for determining monetaryloss due to a difference between the required thermal resistance and thedetermined thermal resistance.
 7. The method of claim 1, wherein thethermal resistance is determined to include conduction, infiltration,and solar radiation components of heat flow.
 8. The method of claim 1,further comprising: periodically updating the thermal resistance,wherein the measurements of inside and outside environments and the oneor more measured energy sources supplied through the building envelopeare monitored in real-time at a predetermined rate of sampling.
 9. Themethod of claim 7, further comprising: autonomously controlling theinside environment with a climate control system, based on theperiodically updated thermal resistance, and a forecasted outsideenvironment.
 10. The method of claim 8, wherein the autonomouscontrolling of the inside environment with the climate control system isfurther based on a thermal mass within the building envelope and avarying cost rate of at least one of the one or more measured energysources.
 11. The method of claim 1, further comprising: determiningvariations in the thermal resistance resulting from variations over timeof at least one of: the inside environment, the outside environment, andone of the measured energy sources.
 12. The method of claim 1, whereinthe one or more measured energy sources includes human occupants, andwherein heat flow through the building envelope produced by the humanoccupants is determined by measured heat signatures of the humanoccupants entering the building envelope.
 13. The method of claim 1,further comprising: monitoring the inside environment with one or moretemperature transducers embedded between layers of material forming thebuilding envelope.
 14. An apparatus comprising one or more processorsand memory storing instructions, that when executed by the one or moreprocessors, cause the apparatus to: receive measurements of inside andoutside environments of the building envelope, and measurements of oneor more measured energy sources supplied through a building envelope;determine an induced heat flow through a building envelope produced bythe one or more measured energy sources; determine a residual heat flowthrough the building envelope based on the induced heat flow and changesin the inside and the outside environments, and determine a thermalresistance of the building envelope based on the calculated residualheat flow and the changes between the inside and the outsideenvironments.
 15. The apparatus of claim 14, wherein the instructions,when executed by the one or more processors, further cause the apparatusto calculate the thermal resistance as a time function of the inside andoutside environments approaching equilibrium, while the one or moremeasured energy sources have been inhibited from entering the buildingenvelope.
 16. The apparatus of claim 15, wherein the thermal resistanceis based on the inside and outside environments measured until theinside environment reaches equilibrium with the outside environment. 17.The apparatus of claim 15, wherein the instructions, when executed bythe one or more processors, further cause the apparatus to determine athermal mass within the building envelope.
 18. The apparatus of claim14, wherein the thermal resistance is determined to include conduction,infiltration, and solar radiation components of heat flow.
 19. Theapparatus of claim 14, wherein the instructions, when executed by theone or more processors, further cause the apparatus to periodicallyupdate the thermal resistance, wherein the measurements of inside andoutside environments and the one or more measured energy sourcessupplied through the building envelope are monitored in real-time at apredetermined rate of sampling.
 20. The apparatus of claim 19, whereinthe instructions, when executed by the one or more processors, furthercause the apparatus to autonomously control the inside environment witha climate control system, based on the periodically updated thermalresistance, and a forecasted outside environment.
 21. The apparatus ofclaim 20, wherein the autonomous controlling of the inside environmentwith the climate control system is further based on a thermal masswithin the building envelope and a varying cost rate of at least one ofthe one or more measured energy sources.
 22. The apparatus of claim 14,wherein the instructions, when executed by the one or more processors,further cause the apparatus to determine variations in the thermalresistance resulting from variations over time of at least one of: theinside environment, the outside environment, and one of the measuredenergy sources.
 23. The apparatus of claim 14, wherein the one or moremeasured energy sources includes human occupants, and wherein heat flowthrough the building envelope produced by the human occupants isdetermined by measured heat signatures of the human occupants enteringthe building envelope.
 24. The apparatus of claim 14, wherein theinstructions, when executed by the one or more processors, further causethe apparatus to monitor the inside environment with one or moretemperature transducers embedded between layers of material forming thebuilding envelope.